Institute of Genomics, University of Tartu, Estonia.
Institute of Molecular and Cell Biology, University of Tartu, Estonia.
Genome Biol Evol. 2021 Apr 5;13(4). doi: 10.1093/gbe/evab039.
Detecting natural selection signals in admixed populations can be problematic since the source of the signal typically dates back prior to the admixture event. On one hand, it is now possible to study various source populations before a particular admixture thanks to the developments in ancient DNA (aDNA) in the last decade. However, aDNA availability is limited to certain geographical regions and the sample sizes and quality of the data might not be sufficient for selection analysis in many cases. In this study, we explore possible ways to improve detection of pre-admixture signals in admixed populations using a local ancestry inference approach. We used masked haplotypes for population branch statistic (PBS) and full haplotypes constructed following our approach from Yelmen et al. (2019) for cross-population extended haplotype homozygosity (XP-EHH), utilizing forward simulations to test the power of our analysis. The PBS results on simulated data showed that using masked haplotypes obtained from ancestry deconvolution instead of the admixed population might improve detection quality. On the other hand, XP-EHH results using the admixed population were better compared with the local ancestry method. We additionally report correlation for XP-EHH scores between source and admixed populations, suggesting that haplotype-based approaches must be used cautiously for recently admixed populations. Additionally, we performed PBS on real South Asian populations masked with local ancestry deconvolution and report here the first possible selection signals on the autochthonous South Asian component of contemporary South Asian populations.
在混合人群中检测自然选择信号可能会有问题，因为信号的来源通常可以追溯到混合事件之前。一方面，由于过去十年中古代 DNA (aDNA) 的发展，现在有可能在特定的混合之前研究各种来源的人群。然而，aDNA 的可用性仅限于某些地理区域，并且在许多情况下，数据的样本量和质量可能不足以进行选择分析。在这项研究中，我们探索了使用局部祖先推断方法在混合人群中提高前混合信号检测的可能方法。我们使用掩蔽单倍型进行群体分支统计 (PBS)，并按照 Yelmen 等人的方法构建完整单倍型 (2019) 进行跨群体扩展单倍型同质性 (XP-EHH)，利用正向模拟来测试我们分析的能力。模拟数据的 PBS 结果表明，使用从祖先反卷积获得的掩蔽单倍型而不是混合群体可能会提高检测质量。另一方面，与局部祖先方法相比，使用混合群体的 XP-EHH 结果更好。我们还报告了源群体和混合群体之间 XP-EHH 得分的相关性，表明基于单倍型的方法必须谨慎用于最近混合的群体。此外，我们使用局部祖先反卷积对真实的南亚人群进行了 PBS，并在此报告了当代南亚人群中本地南亚成分上的第一个可能的选择信号。
